

from collections import OrderedDict
from typing import Mapping

from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging


A_			:					Union[str, Any]    			=     logging.get_logger(__name__)

A_			:					Optional[int]    			=     {
    'roberta-base': 'https://huggingface.co/roberta-base/resolve/main/config.json',
    'roberta-large': 'https://huggingface.co/roberta-large/resolve/main/config.json',
    'roberta-large-mnli': 'https://huggingface.co/roberta-large-mnli/resolve/main/config.json',
    'distilroberta-base': 'https://huggingface.co/distilroberta-base/resolve/main/config.json',
    'roberta-base-openai-detector': 'https://huggingface.co/roberta-base-openai-detector/resolve/main/config.json',
    'roberta-large-openai-detector': 'https://huggingface.co/roberta-large-openai-detector/resolve/main/config.json',
}



class        _a		(_A							):


					'''simple docstring'''






					UpperCAmelCase__:  Union[str, Any]    				=			'''roberta'''






					def __init__(					self       ,			A__=5_0265       ,			A__=768       ,			A__=12       ,			A__=12       ,			A__=3072       ,			A__="gelu"       ,			A__=0.1       ,			A__=0.1       ,			A__=512       ,			A__=2       ,			A__=0.0_2       ,			A__=1e-12       ,			A__=1       ,			A__=0       ,			A__=2       ,			A__="absolute"       ,			A__=True       ,			A__=None       ,			**A__       ,			):
						super().__init__(pad_token_id=a_       ,			bos_token_id=a_       ,			eos_token_id=a_       ,			**a_     )

						A__				:       List[Any]	  =						vocab_size
						A__				:       Dict	  =						hidden_size
						A__				:       List[Any]	  =						num_hidden_layers
						A__				:       Dict	  =						num_attention_heads
						A__				:       Dict	  =						hidden_act
						A__				:       List[Any]	  =						intermediate_size
						A__				:       Any	  =						hidden_dropout_prob
						A__				:       Dict	  =						attention_probs_dropout_prob
						A__				:       Optional[int]	  =						max_position_embeddings
						A__				:       Optional[int]	  =						type_vocab_size
						A__				:       Optional[int]	  =						initializer_range
						A__				:       str	  =						layer_norm_eps
						A__				:       Tuple	  =						position_embedding_type
						A__				:       Tuple	  =						use_cache
						A__				:       List[str]	  =						classifier_dropout



class        _a		(_A							):


					'''simple docstring'''






					@property
					def     __A     (					self     ):
						if self.task == "multiple-choice":
							A__				:       str	  =						{0: "batch", 1: "choice", 2: "sequence"}
						else:
							A__				:       str	  =						{0: "batch", 1: "sequence"}
						return OrderedDict(
						    [
						        ("""input_ids""", dynamic_axis),
						        ("""attention_mask""", dynamic_axis),
						    ]     )










'''simple docstring'''






lowerCAmelCase									=   [sum(int(c, 10) ** 2 for c in i.__str__()) for i in range(10_00_00)]






def   __A    (				a_    :	int						):
		lowerCAmelCase  :     Optional[int]       						= 0
		while number:
				# Increased Speed Slightly by checking every 5 digits together.
				sum_of_digits_squared += DIGITS_SQUARED[number % 1_0_0_0_0_0]
				number //= 1_0_0_0_0_0

		return sum_of_digits_squared


# There are 2 Chains made,
# One ends with 89 with the chain member 58 being the one which when declared first,
# there will be the least number of iterations for all the members to be checked.

# The other one ends with 1 and has only one element 1.

# So 58 and 1 are chosen to be declared at the starting.

# Changed dictionary to an array to quicken the solution
lowerCAmelCase									=   [None] * 10_00_00_00
lowerCAmelCase									=   True
lowerCAmelCase									=   False






def   __A    (				a_    :	int						):

		if CHAINS[number - 1] is not None:
				return CHAINS[number - 1]  # type: ignore

		lowerCAmelCase  :     Dict       						= chain(next_number(a_						)						)
		lowerCAmelCase  :     Union[str, Any]       						= number_chain

		while number < 1_0_0_0_0_0_0_0:
				lowerCAmelCase  :     Any       						= number_chain
				number *= 1_0

		return number_chain






def   __A    (				a_    :	int = 1_0_0_0_0_0_0_0						):
		for i in range(1   ,a_						):
				if CHAINS[i] is None:
						chain(i + 1						)

		return CHAINS[:number].count(a_						)


if __name__ == "__main__":
					import doctest

					doctest.testmod()
					print(F'''{solution() = }''')



